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Attempts to theorize the relationship between the informal and the illegal sectors of the economy. States that there are significant behavioural similarities. Proposes an emergent paradigm based on dual labour market theory to explain the similarites and differences in order to guide future research in each area. Applies the theory to the production and marketing of crack cocaine and shows how the model helps us to understand issues of exploitation and risk makagement within the drug market.

During the 1990s, the New York City Police Department (NYPD) instituted a policy of arresting and detaining people for minor offenses that occur in public as part of their quality‐of‐life (QOL) policing initiative. The purpose of this paper is to examine the pros and cons of the current policy and compare it with possible alternatives including: arrest and issuing of a desk appearance ticket (DAT); issuing of a non‐criminal citation (violation); street warnings; and toleration of public marijuana smoking.

The paper reviews several studies of QOL policing and examines the pros and cons of the current NYPD policy, compared to possible alternatives.

The number of NYPD arrests for marijuana in public view (MPV) (with most detained for one or two days) increased from 3,000 in 1994 to over 50,000 in 2000, and have been about 30,000 in the mid‐2000s. Most of these arrestees (84 percent) were minority; Blacks were 2.7 more likely and Hispanics 1.8 times more likely to be detained than Whites for an MPV arrest. Minorities received more severe dispositions, even controlling for demographics and prior arrest histories.

The paper recommends that the NYPD change to routinely issuing DATs to reduce detention for marijuana violators. Drug policy reformers might wish to further pursue changing statutes regarding smoking MPV into a violation (non‐criminal) or encourage the wider use of street warnings, as in Britain. Any of these policy changes would help reduce the number detained and the disproportionate burden on minorities associated with the current arrest and detention policy. These policies could help maintain civic norms against smoking marijuana in public.

Purpose – In this chapter, we expand the definition of disaster through combining the tenets of disaster studies with the literature on risks and consequences of war and conflict-related displacement and dislocation, with a focus on the challenges that drug misuse and changing drug markets present in these contexts. We conclude with policy recommendations for successful community rebuilding with relation to drugs and drug markets following various forms of disaster, gleaned from the combination of these areas of inquiry.

Design/methodology/approach – We discuss the concepts of risk, social vulnerability, and consequences as related to traditional conceptualizations of disaster, and highlight how they can also be applied to the study of veterans returning from war. We focus the on the similarities related to drugs and drug markets.

Findings – Overall, the similar vulnerabilities, potential for trauma, and drug-related consequences experienced by both disaster survivors and veterans suggest that the experience of war and return from such an event could be considered a disaster and analyzed as such.

Originality/value of power – Few scholars have examined how to expand the definition of a disaster and what is examined in the field of disaster studies. This chapter does this by examining how war could be analyzed as a disaster. It demonstrates the parallels between war and traditional disaster.

In the 1990s, the New York City Police Department expanded its focus on reducing behaviors that detract from the overall quality of life (QOL) in the city. Many have credited this effort for the decline in the city's overall crime rate. They often cite the fixing broken windows argument, which maintains that reducing disorder sets off a chain of events leading to less crime. However, systematic research has not yet documented this chain of events. Looks at one of the first linkages, whether QOL policing sends a message to offenders not to engage in disorderly behaviors in public locales. The project interviewed 539 New York City arrestees in 1999. Almost all of them were aware that police were targeting various disorderly behaviors. Among those that engaged in disorderly behaviors, about half reported that they had stopped or cut back in the past six months. They reported a police presence was the most important factor behind their behavioral changes. These findings support the idea that QOL policing has a deterrent effect.

The purpose of this paper is to examine the experiences of poor drug users and sellers who remained in New Orleans during Hurricane Katrina in 2005 to identify their special needs and the unique challenges they present to disaster management.

Semi‐structured, open‐ended interviews were conducted with 119 poor, predominantly African‐American, drug users and sellers. Their stories in their own words provide a mosaic of drug‐related experiences from the period immediately preceding the storm through evacuation and reveal the motivations behind their behaviors.

Many drug users placed partying, maintaining their habits, and making money ahead of personal safety and evacuation. Drug use and sales led many not to evacuate before the storm, to use drugs in congregate shelters, to avoid shelters, to roam through flooded debris‐strewn streets, to loot stores and homes of drug dealers, and to use violence or the threat of violence to achieve their drug‐related aims.

During a disaster, many poor drug users place risks on themselves, their families, their communities and ultimately on rescue workers. The conclusion presents pragmatic and humanitarian guidelines for successfully addressing this additional challenge. The recommendations are consistent with other suggestions concerning the special needs of indigent populations.

Extends the notion of informality into the area of illegality, looking at how illegal crack vendors in New York use informality to reduce and pass risk to others. Focuses on the techniques used to avoid detection and arrest and the methods of placing risk of imprisonment on smaller, lower‐income dealers. Suggests that this process of exploitation only makes sense when seen in the broader context of inequality in US society where some have nothing to lose by going to jail.

In view of the global warming that has increasingly been plaguing the earth, it should be no surprise that the world has been witnessing an unprecedented wave of natural disasters over the past decades. Among the most important of these natural calamities in recent years, mention can be made of the Indian Ocean earthquake and tsunami of 2004, hurricanes Katrina and Irene in the United States in 2005, cyclone Nargis in Burma in 2008, the Haiti earthquake of 2010, the Russian heat wave of 2010, the 2011 tornado in Joplin, Missouri, and the 2011 Tōhoku earthquake and tsunami in Japan. Ranging from earthquakes, volcanic eruptions, avalanches, and floods to heat waves, storms, and epidemics, the field of disaster research presents a myriad of questions for social-scientific exploration.

In this study, we analyze the power of the individual return-to-volatility security performance heuristic (ri/stdi) to simplify the identification of securities to buy and, consequently, to form the optimal no short sales mean–variance portfolios. The heuristic ri/stdi is powerful enough to identify the long and shorts sets. This is due to the positive definiteness of the variance–covariance matrix – the key is to use the heuristic sequentially. At the investor level, the heuristic helps investors to decide what securities to consider first. At the portfolio level, the heuristic may help us find out whether it is a good idea to invest in equity to begin with. Our research may also help to integrate individual security analysis into portfolio optimization through improved security rankings.

Value‐at‐Risk (VaR) has become a mainstream risk management technique employed by a large proportion of financial institutions. There exists a substantial amount of research dealing with this task, most commonly referred to as VaR backtesting. A new generation of “self‐learning” VaR models (Conditional Autoregressive Value‐at‐Risk or CAViaR) combine backtesting results with ex ante VaR estimates in an ARIMA framework in order to forecast P/L distributions more accurately. In this commentary, the authors present a systematic overview of several classes of applied statistical techniques that can make VaR backtesting more comprehensive and provide valuable insights into the analytical properties of VaR models in various market environments. In addition, they discuss the challenges associated with extending traditional backtesting approaches for VaR horizons longer than one day and propose solutions to this important problem.